Pandas Profiling Report

Dataset statistics

Number of variables	14
Number of observations	20000
Missing cells	42841
Missing cells (%)	15.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	2.0 MiB
Average record size in memory	104.0 B

Variable types

Numeric	8
Categorical	5
Boolean	1

Warnings

`car_type` has a high cardinality: 373 distinct values	High cardinality
`average_price` is highly correlated with `price`	High correlation
`price` is highly correlated with `average_price` and 1 other fields	High correlation
`diff_price` is highly correlated with `price` and 1 other fields	High correlation
`diff_price_perc` is highly correlated with `diff_price`	High correlation
`average_price` is highly correlated with `price`	High correlation
`price` is highly correlated with `average_price` and 1 other fields	High correlation
`diff_price` is highly correlated with `price` and 1 other fields	High correlation
`diff_price_perc` is highly correlated with `diff_price`	High correlation
`average_price` is highly correlated with `price`	High correlation
`price` is highly correlated with `average_price` and 1 other fields	High correlation
`diff_price` is highly correlated with `price` and 1 other fields	High correlation
`diff_price_perc` is highly correlated with `diff_price`	High correlation
`antiquity` is highly correlated with `card_brand`	High correlation
`price` is highly correlated with `card_brand` and 1 other fields	High correlation
`card_brand` is highly correlated with `antiquity` and 3 other fields	High correlation
`average_price` is highly correlated with `price` and 1 other fields	High correlation
`km` is highly correlated with `card_brand`	High correlation
`DI` has 14280 (71.4%) missing values	Missing
`price` has 14280 (71.4%) missing values	Missing
`sold` has 14280 (71.4%) missing values	Missing
`car_id` is uniformly distributed	Uniform
`antiquity` has 447 (2.2%) zeros	Zeros

Reproduction

Analysis started	2021-05-29 22:35:05.943004
Analysis finished	2021-05-29 22:40:20.643353
Duration	5 minutes and 14.7 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

car_id
Real number (ℝ_≥0)

UNIFORM

Distinct	19999
Distinct (%)	100.0%
Missing	1
Missing (%)	< 0.1%
Infinite	0
Infinite (%)	0.0%
Mean	9999.498575

Minimum	0
Maximum	19999
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	0
5-th percentile	999.9
Q1	4999.5
median	9999
Q3	14999.5
95-th percentile	18999.1
Maximum	19999
Range	19999
Interquartile range (IQR)	10000

Descriptive statistics

Standard deviation	5773.791378
Coefficient of variation (CV)	0.5774080905
Kurtosis	-1.200090018
Mean	9999.498575
Median Absolute Deviation (MAD)	5000
Skewness	7.405197625 × 10^-7
Sum	199979972
Variance	33336666.88
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
820	1	< 0.1%
7592	1	< 0.1%
10842	1	< 0.1%
13762	1	< 0.1%
4871	1	< 0.1%
18356	1	< 0.1%
5108	1	< 0.1%
262	1	< 0.1%
14230	1	< 0.1%
Other values (19989)	19989	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
19999	1	< 0.1%
19998	1	< 0.1%
19997	1	< 0.1%
19996	1	< 0.1%
19995	1	< 0.1%
19994	1	< 0.1%
19993	1	< 0.1%
19992	1	< 0.1%
19991	1	< 0.1%
19990	1	< 0.1%

car_type
Categorical

HIGH CARDINALITY

Distinct	373
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Memory size	156.4 KiB

Serie 1	180
Ram 1500 V6	171
Odyssey	153
Transit	149
Saveiro	148
Other values (368)	19199

Length

Max length	25
Median length	6
Mean length	6.88445
Min length	2

Characters and Unicode

Total characters	137689
Distinct characters	65
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Supra
2nd row	Supra
3rd row	Supra
4th row	Supra
5th row	Supra

Common Values

Value	Count	Frequency (%)
Serie 1	180	0.9%
Ram 1500 V6	171	0.9%
Odyssey	153	0.8%
Transit	149	0.7%
Saveiro	148	0.7%
Terrain	147	0.7%
CR-V	145	0.7%
March	144	0.7%
Serie 7	141	0.7%
Civic	140	0.7%
Other values (363)	18482	92.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
clase	1022	3.7%
serie	749	2.7%
van	368	1.3%
ram	368	1.3%
cargo	364	1.3%
quattro	336	1.2%
range	306	1.1%
rover	306	1.1%
v6	306	1.1%
1500	284	1.0%
Other values (380)	23059	83.9%

Most occurring characters

Value	Count	Frequency (%)
a	12832	9.3%
e	11185	8.1%
r	10843	7.9%
	7547	5.5%
o	6787	4.9%
i	6251	4.5%
n	5753	4.2%
t	5438	3.9%
C	4808	3.5%
s	4396	3.2%
Other values (55)	61849	44.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	87438	63.5%
Uppercase Letter	30354	22.0%
Decimal Number	11751	8.5%
Space Separator	7547	5.5%
Dash Punctuation	599	0.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	12832	14.7%
e	11185	12.8%
r	10843	12.4%
o	6787	7.8%
i	6251	7.1%
n	5753	6.6%
t	5438	6.2%
s	4396	5.0%
l	3310	3.8%
u	2671	3.1%
Other values (17)	17972	20.6%

Uppercase Letter

Value	Count	Frequency (%)
C	4808	15.8%
S	4181	13.8%
R	2322	7.6%
M	1899	6.3%
T	1846	6.1%
V	1620	5.3%
A	1590	5.2%
L	1543	5.1%
X	1542	5.1%
E	1368	4.5%
Other values (16)	7635	25.2%

Decimal Number

Value	Count	Frequency (%)
0	3902	33.2%
5	1610	13.7%
3	1136	9.7%
1	963	8.2%
6	893	7.6%
4	890	7.6%
8	854	7.3%
2	772	6.6%
7	616	5.2%
9	115	1.0%

Space Separator

Value	Count	Frequency (%)
	7547	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	599	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	117792	85.5%
Common	19897	14.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	12832	10.9%
e	11185	9.5%
r	10843	9.2%
o	6787	5.8%
i	6251	5.3%
n	5753	4.9%
t	5438	4.6%
C	4808	4.1%
s	4396	3.7%
S	4181	3.5%
Other values (43)	45318	38.5%

Common

Value	Count	Frequency (%)
	7547	37.9%
0	3902	19.6%
5	1610	8.1%
3	1136	5.7%
1	963	4.8%
6	893	4.5%
4	890	4.5%
8	854	4.3%
2	772	3.9%
7	616	3.1%
Other values (2)	714	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	137663	> 99.9%
Latin 1 Sup	26	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	12832	9.3%
e	11185	8.1%
r	10843	7.9%
	7547	5.5%
o	6787	4.9%
i	6251	4.5%
n	5753	4.2%
t	5438	4.0%
C	4808	3.5%
s	4396	3.2%
Other values (54)	61823	44.9%

Latin 1 Sup

Value	Count	Frequency (%)
ó	26	100.0%

color
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	156.4 KiB

Black	6991
White	5048
Red	4043
Blue	3315
Orange	603

Length

Max length	6
Median length	5
Mean length	4.4601
Min length	3

Characters and Unicode

Total characters	89202
Distinct characters	17
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Blue
2nd row	Black
3rd row	Black
4th row	Blue
5th row	Black

Common Values

Value	Count	Frequency (%)
Black	6991	35.0%
White	5048	25.2%
Red	4043	20.2%
Blue	3315	16.6%
Orange	603	3.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
black	6991	35.0%
white	5048	25.2%
red	4043	20.2%
blue	3315	16.6%
orange	603	3.0%

Most occurring characters

Value	Count	Frequency (%)
e	13009	14.6%
B	10306	11.6%
l	10306	11.6%
a	7594	8.5%
c	6991	7.8%
k	6991	7.8%
W	5048	5.7%
h	5048	5.7%
i	5048	5.7%
t	5048	5.7%
Other values (7)	13813	15.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	69202	77.6%
Uppercase Letter	20000	22.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	13009	18.8%
l	10306	14.9%
a	7594	11.0%
c	6991	10.1%
k	6991	10.1%
h	5048	7.3%
i	5048	7.3%
t	5048	7.3%
d	4043	5.8%
u	3315	4.8%
Other values (3)	1809	2.6%

Uppercase Letter

Value	Count	Frequency (%)
B	10306	51.5%
W	5048	25.2%
R	4043	20.2%
O	603	3.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	89202	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	13009	14.6%
B	10306	11.6%
l	10306	11.6%
a	7594	8.5%
c	6991	7.8%
k	6991	7.8%
W	5048	5.7%
h	5048	5.7%
i	5048	5.7%
t	5048	5.7%
Other values (7)	13813	15.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	89202	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	13009	14.6%
B	10306	11.6%
l	10306	11.6%
a	7594	8.5%
c	6991	7.8%
k	6991	7.8%
W	5048	5.7%
h	5048	5.7%
i	5048	5.7%
t	5048	5.7%
Other values (7)	13813	15.5%

km
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	19993
Distinct (%)	> 99.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	25259639.99

Minimum	1394070
Maximum	49452737
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	78.2 KiB

Quantile statistics

Minimum	1394070
5-th percentile	10611032.15
Q1	18958897.75
median	25294503
Q3	31499937.5
95-th percentile	40072602.05
Maximum	49452737
Range	48058667
Interquartile range (IQR)	12541039.75

Descriptive statistics

Standard deviation	8917901.232
Coefficient of variation (CV)	0.3530494194
Kurtosis	-0.4508520235
Mean	25259639.99
Median Absolute Deviation (MAD)	6269228.5
Skewness	0.02030405366
Sum	5.051927997 × 10¹¹
Variance	7.952896238 × 10¹³
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22008680	2	< 0.1%
21151223	2	< 0.1%
35675327	2	< 0.1%
18804442	2	< 0.1%
30179528	2	< 0.1%
26147715	2	< 0.1%
28361231	2	< 0.1%
13376841	1	< 0.1%
30264659	1	< 0.1%
26756434	1	< 0.1%
Other values (19983)	19983	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1394070	1	< 0.1%
1620426	1	< 0.1%
1646143	1	< 0.1%
1660807	1	< 0.1%
1708590	1	< 0.1%
1818247	1	< 0.1%
1859642	1	< 0.1%
1890364	1	< 0.1%
1891943	1	< 0.1%
2045134	1	< 0.1%

Value	Count	Frequency (%)
49452737	1	< 0.1%
49416201	1	< 0.1%
49404285	1	< 0.1%
49061130	1	< 0.1%
48822502	1	< 0.1%
48707264	1	< 0.1%
48695728	1	< 0.1%
48648519	1	< 0.1%
48617054	1	< 0.1%
48570426	1	< 0.1%

average_price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	700
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	551491.0049

Minimum	101729
Maximum	997705
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	101729
5-th percentile	149481
Q1	330625
median	559715
Q3	781472
95-th percentile	951729
Maximum	997705
Range	895976
Interquartile range (IQR)	450847

Descriptive statistics

Standard deviation	257113.0326
Coefficient of variation (CV)	0.4662143721
Kurtosis	-1.209466392
Mean	551491.0049
Median Absolute Deviation (MAD)	226560
Skewness	-0.02910769406
Sum	1.10298201 × 10¹⁰
Variance	6.610711154 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
307812	48	0.2%
238184	44	0.2%
469923	43	0.2%
133420	43	0.2%
121909	42	0.2%
598395	41	0.2%
997067	40	0.2%
196372	40	0.2%
820251	40	0.2%
207391	40	0.2%
Other values (690)	19579	97.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
101729	34	0.2%
102486	22	0.1%
106132	29	0.1%
106227	30	0.1%
107583	24	0.1%
108056	32	0.2%
112643	22	0.1%
117277	28	0.1%
120985	29	0.1%
121909	42	0.2%

Value	Count	Frequency (%)
997705	21	0.1%
997104	28	0.1%
997067	40	0.2%
993481	25	0.1%
992179	26	0.1%
992167	29	0.1%
990878	17	0.1%
988968	23	0.1%
986711	32	0.2%
986078	33	0.2%

transmission
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	156.4 KiB

Automatic	15874
Manual	4126

Length

Max length	9
Median length	9
Mean length	8.3811
Min length	6

Characters and Unicode

Total characters	167622
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Manual
2nd row	Manual
3rd row	Manual
4th row	Manual
5th row	Manual

Common Values

Value	Count	Frequency (%)
Automatic	15874	79.4%
Manual	4126	20.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
automatic	15874	79.4%
manual	4126	20.6%

Most occurring characters

Value	Count	Frequency (%)
t	31748	18.9%
a	24126	14.4%
u	20000	11.9%
A	15874	9.5%
o	15874	9.5%
m	15874	9.5%
i	15874	9.5%
c	15874	9.5%
M	4126	2.5%
n	4126	2.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	147622	88.1%
Uppercase Letter	20000	11.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	31748	21.5%
a	24126	16.3%
u	20000	13.5%
o	15874	10.8%
m	15874	10.8%
i	15874	10.8%
c	15874	10.8%
n	4126	2.8%
l	4126	2.8%

Uppercase Letter

Value	Count	Frequency (%)
A	15874	79.4%
M	4126	20.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	167622	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	31748	18.9%
a	24126	14.4%
u	20000	11.9%
A	15874	9.5%
o	15874	9.5%
m	15874	9.5%
i	15874	9.5%
c	15874	9.5%
M	4126	2.5%
n	4126	2.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	167622	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	31748	18.9%
a	24126	14.4%
u	20000	11.9%
A	15874	9.5%
o	15874	9.5%
m	15874	9.5%
i	15874	9.5%
c	15874	9.5%
M	4126	2.5%
n	4126	2.5%

body_type
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	156.4 KiB

Sedan	11780
SUV	4943
Coupe	2371
Truck	906

Length

Max length	5
Median length	5
Mean length	4.5057
Min length	3

Characters and Unicode

Total characters	90114
Distinct characters	15
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Sedan
2nd row	Sedan
3rd row	Sedan
4th row	Sedan
5th row	Sedan

Common Values

Value	Count	Frequency (%)
Sedan	11780	58.9%
SUV	4943	24.7%
Coupe	2371	11.9%
Truck	906	4.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
sedan	11780	58.9%
suv	4943	24.7%
coupe	2371	11.9%
truck	906	4.5%

Most occurring characters

Value	Count	Frequency (%)
S	16723	18.6%
e	14151	15.7%
d	11780	13.1%
a	11780	13.1%
n	11780	13.1%
U	4943	5.5%
V	4943	5.5%
u	3277	3.6%
C	2371	2.6%
o	2371	2.6%
Other values (5)	5995	6.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	60228	66.8%
Uppercase Letter	29886	33.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	14151	23.5%
d	11780	19.6%
a	11780	19.6%
n	11780	19.6%
u	3277	5.4%
o	2371	3.9%
p	2371	3.9%
r	906	1.5%
c	906	1.5%
k	906	1.5%

Uppercase Letter

Value	Count	Frequency (%)
S	16723	56.0%
U	4943	16.5%
V	4943	16.5%
C	2371	7.9%
T	906	3.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	90114	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
S	16723	18.6%
e	14151	15.7%
d	11780	13.1%
a	11780	13.1%
n	11780	13.1%
U	4943	5.5%
V	4943	5.5%
u	3277	3.6%
C	2371	2.6%
o	2371	2.6%
Other values (5)	5995	6.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	90114	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
S	16723	18.6%
e	14151	15.7%
d	11780	13.1%
a	11780	13.1%
n	11780	13.1%
U	4943	5.5%
V	4943	5.5%
u	3277	3.6%
C	2371	2.6%
o	2371	2.6%
Other values (5)	5995	6.7%

DI
Real number (ℝ_≥0)

MISSING

Distinct	99
Distinct (%)	1.7%
Missing	14280
Missing (%)	71.4%
Infinite	0
Infinite (%)	0.0%
Mean	22.91468531

Minimum	1
Maximum	131
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	9
median	20
Q3	34
95-th percentile	55.05
Maximum	131
Range	130
Interquartile range (IQR)	25

Descriptive statistics

Standard deviation	17.35294604
Coefficient of variation (CV)	0.7572849376
Kurtosis	1.26195219
Mean	22.91468531
Median Absolute Deviation (MAD)	12
Skewness	1.013808371
Sum	131072
Variance	301.1247362
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	199	1.0%
2	198	1.0%
3	193	1.0%
4	184	0.9%
5	166	0.8%
8	158	0.8%
7	158	0.8%
6	156	0.8%
10	149	0.7%
13	140	0.7%
Other values (89)	4019	20.1%
(Missing)	14280	71.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	199	1.0%
2	198	1.0%
3	193	1.0%
4	184	0.9%
5	166	0.8%
6	156	0.8%
7	158	0.8%
8	158	0.8%
9	137	0.7%
10	149	0.7%

Value	Count	Frequency (%)
131	1	< 0.1%
115	1	< 0.1%
113	1	< 0.1%
111	1	< 0.1%
107	2	< 0.1%
105	1	< 0.1%
101	1	< 0.1%
99	1	< 0.1%
96	1	< 0.1%
95	3	< 0.1%

price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5703
Distinct (%)	99.7%
Missing	14280
Missing (%)	71.4%
Infinite	0
Infinite (%)	0.0%
Mean	598836.383

Minimum	98972
Maximum	1163319
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	98972
5-th percentile	158602.25
Q1	348538.5
median	612722.5
Q3	841746.5
95-th percentile	1030949.35
Maximum	1163319
Range	1064347
Interquartile range (IQR)	493208

Descriptive statistics

Standard deviation	280196.5412
Coefficient of variation (CV)	0.4679016659
Kurtosis	-1.157495585
Mean	598836.383
Median Absolute Deviation (MAD)	244683.5
Skewness	-0.02344815849
Sum	3425344111
Variance	7.85101017 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
541157	2	< 0.1%
756074	2	< 0.1%
330452	2	< 0.1%
301604	2	< 0.1%
878839	2	< 0.1%
1126603	2	< 0.1%
431924	2	< 0.1%
590043	2	< 0.1%
601971	2	< 0.1%
332308	2	< 0.1%
Other values (5693)	5700	28.5%
(Missing)	14280	71.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
98972	1	< 0.1%
104134	1	< 0.1%
104470	1	< 0.1%
104567	1	< 0.1%
104792	1	< 0.1%
104901	1	< 0.1%
105214	1	< 0.1%
106935	1	< 0.1%
107601	1	< 0.1%
108137	1	< 0.1%

Value	Count	Frequency (%)
1163319	1	< 0.1%
1160698	1	< 0.1%
1157642	1	< 0.1%
1157226	1	< 0.1%
1155358	1	< 0.1%
1155009	1	< 0.1%
1154296	1	< 0.1%
1151789	1	< 0.1%
1151026	1	< 0.1%
1147208	1	< 0.1%

sold
Boolean

MISSING

Distinct	2
Distinct (%)	< 0.1%
Missing	14280
Missing (%)	71.4%
Memory size	156.4 KiB

True	4738
False	982
(Missing)	14280

Common Values
Chart

Value	Count	Frequency (%)
True	4738	23.7%
False	982	4.9%
(Missing)	14280	71.4%

diff_price
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5577
Distinct (%)	27.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-721226593.8

Minimum	-1010101010
Maximum	11625
Zeros	0
Zeros (%)	0.0%
Negative	19970
Negative (%)	99.9%
Memory size	156.4 KiB

Quantile statistics

Minimum	-1010101010
5-th percentile	-1010101010
Q1	-1010101010
median	-1010101010
Q3	-101063.5
95-th percentile	-14205.35
Maximum	11625
Range	1010112635
Interquartile range (IQR)	1009999946

Descriptive statistics

Standard deviation	456442450.4
Coefficient of variation (CV)	-0.6328696895
Kurtosis	-1.102911981
Mean	-721226593.8
Median Absolute Deviation (MAD)	0
Skewness	0.9472055271
Sum	-1.442453188 × 10¹³
Variance	2.083397106 × 10¹⁷
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-1010101010	14280	71.4%
-11891	3	< 0.1%
-46136	3	< 0.1%
-42756	3	< 0.1%
-20586	3	< 0.1%
-10076	2	< 0.1%
-24753	2	< 0.1%
-41817	2	< 0.1%
-87682	2	< 0.1%
-78492	2	< 0.1%
Other values (5567)	5698	28.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1010101010	14280	71.4%
-172441	1	< 0.1%
-171780	1	< 0.1%
-171577	1	< 0.1%
-170454	1	< 0.1%
-166885	1	< 0.1%
-166759	1	< 0.1%
-166449	1	< 0.1%
-166188	1	< 0.1%
-165463	1	< 0.1%

Value	Count	Frequency (%)
11625	1	< 0.1%
10314	1	< 0.1%
8611	1	< 0.1%
4585	1	< 0.1%
3788	1	< 0.1%
2807	1	< 0.1%
2780	1	< 0.1%
2580	1	< 0.1%
2544	1	< 0.1%
2330	1	< 0.1%

diff_price_perc
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5720
Distinct (%)	28.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-721212121.2

Minimum	-1010101010
Maximum	0.08004052685
Zeros	0
Zeros (%)	0.0%
Negative	19970
Negative (%)	99.9%
Memory size	156.4 KiB

Quantile statistics

Minimum	-1010101010
5-th percentile	-1010101010
Q1	-1010101010
median	-1010101010
Q3	-0.1536200889
95-th percentile	-0.03649030825
Maximum	0.08004052685
Range	1010101010
Interquartile range (IQR)	1010101010

Descriptive statistics

Standard deviation	456465317.7
Coefficient of variation (CV)	-0.6329140961
Kurtosis	-1.102912003
Mean	-721212121.2
Median Absolute Deviation (MAD)	0
Skewness	0.9472055205
Sum	-1.442424242 × 10¹³
Variance	2.083605863 × 10¹⁷
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-1010101010	14280	71.4%
-0.1388262657	2	< 0.1%
-0.112023407	1	< 0.1%
-0.05641811086	1	< 0.1%
-0.02205650444	1	< 0.1%
-0.06856298648	1	< 0.1%
-0.1504964129	1	< 0.1%
-0.0356024219	1	< 0.1%
-0.05228106806	1	< 0.1%
-0.1604710707	1	< 0.1%
Other values (5710)	5710	28.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1010101010	14280	71.4%
-0.179995194	1	< 0.1%
-0.1795523103	1	< 0.1%
-0.179354543	1	< 0.1%
-0.1790841369	1	< 0.1%
-0.178711864	1	< 0.1%
-0.1786377849	1	< 0.1%
-0.1784605023	1	< 0.1%
-0.178431125	1	< 0.1%
-0.1784283832	1	< 0.1%

Value	Count	Frequency (%)
0.08004052685	1	< 0.1%
0.05146629124	1	< 0.1%
0.05110190654	1	< 0.1%
0.03047416775	1	< 0.1%
0.02271691308	1	< 0.1%
0.01687649833	1	< 0.1%
0.0133825007	1	< 0.1%
0.01293917793	1	< 0.1%
0.01278290856	1	< 0.1%
0.01171182178	1	< 0.1%

card_brand
Categorical

HIGH CORRELATION

Distinct	47
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	156.4 KiB

Nissan	1413
Mercedes Benz	1412
Chevrolet	1316
Ford	1288
Volkswagen	1189
Other values (42)	13382

Length

Max length	13
Median length	6
Mean length	6.46825
Min length	3

Characters and Unicode

Total characters	129365
Distinct characters	43
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Toyota
2nd row	Toyota
3rd row	Toyota
4th row	Toyota
5th row	Toyota

Common Values

Value	Count	Frequency (%)
Nissan	1413	7.1%
Mercedes Benz	1412	7.1%
Chevrolet	1316	6.6%
Ford	1288	6.4%
Volkswagen	1189	5.9%
Audi	1167	5.8%
Dodge	1131	5.7%
BMW	990	5.0%
Honda	968	4.8%
Toyota	935	4.7%
Other values (37)	8191	41.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
nissan	1413	6.4%
benz	1412	6.4%
mercedes	1412	6.4%
chevrolet	1316	6.0%
ford	1288	5.9%
volkswagen	1189	5.4%
audi	1167	5.3%
dodge	1131	5.2%
bmw	990	4.5%
honda	968	4.4%
Other values (38)	9651	44.0%

Most occurring characters

Value	Count	Frequency (%)
e	15072	11.7%
o	10715	8.3%
a	9097	7.0%
n	7672	5.9%
d	7184	5.6%
s	6901	5.3%
r	6161	4.8%
i	6099	4.7%
t	4894	3.8%
u	4778	3.7%
Other values (33)	50792	39.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	101996	78.8%
Uppercase Letter	25399	19.6%
Space Separator	1970	1.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	15072	14.8%
o	10715	10.5%
a	9097	8.9%
n	7672	7.5%
d	7184	7.0%
s	6901	6.8%
r	6161	6.0%
i	6099	6.0%
t	4894	4.8%
u	4778	4.7%
Other values (13)	23423	23.0%

Uppercase Letter

Value	Count	Frequency (%)
M	3702	14.6%
B	2730	10.7%
C	2275	9.0%
A	1734	6.8%
V	1610	6.3%
F	1455	5.7%
N	1413	5.6%
H	1273	5.0%
R	1136	4.5%
D	1131	4.5%
Other values (9)	6940	27.3%

Space Separator

Value	Count	Frequency (%)
	1970	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	127395	98.5%
Common	1970	1.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	15072	11.8%
o	10715	8.4%
a	9097	7.1%
n	7672	6.0%
d	7184	5.6%
s	6901	5.4%
r	6161	4.8%
i	6099	4.8%
t	4894	3.8%
u	4778	3.8%
Other values (32)	48822	38.3%

Common

Value	Count	Frequency (%)
	1970	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	129365	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	15072	11.7%
o	10715	8.3%
a	9097	7.0%
n	7672	5.9%
d	7184	5.6%
s	6901	5.3%
r	6161	4.8%
i	6099	4.7%
t	4894	3.8%
u	4778	3.7%
Other values (33)	50792	39.3%

antiquity
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	14
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.69675

Minimum	0
Maximum	13
Zeros	447
Zeros (%)	2.2%
Negative	0
Negative (%)	0.0%
Memory size	78.2 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	3
median	7
Q3	10
95-th percentile	13
Maximum	13
Range	13
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	3.853197606
Coefficient of variation (CV)	0.5753832242
Kurtosis	-1.190904861
Mean	6.69675
Median Absolute Deviation (MAD)	3
Skewness	0.02676276959
Sum	133935
Variance	14.84713179
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
9	1823	9.1%
1	1759	8.8%
3	1670	8.3%
8	1597	8.0%
4	1577	7.9%
13	1498	7.5%
5	1463	7.3%
12	1447	7.2%
7	1445	7.2%
10	1421	7.1%
Other values (4)	4300	21.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	447	2.2%
1	1759	8.8%
2	1414	7.1%
3	1670	8.3%
4	1577	7.9%
5	1463	7.3%
6	1292	6.5%
7	1445	7.2%
8	1597	8.0%
9	1823	9.1%

Value	Count	Frequency (%)
13	1498	7.5%
12	1447	7.2%
11	1147	5.7%
10	1421	7.1%
9	1823	9.1%
8	1597	8.0%
7	1445	7.2%
6	1292	6.5%
5	1463	7.3%
4	1577	7.9%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	car_id	car_type	color	km	average_price	transmission	body_type	DI	price	sold	diff_price	diff_price_perc	card_brand	antiquity
0	0	Supra	Blue	25848512	194799.0	Manual	Sedan	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Toyota	1
1	112	Supra	Black	25913421	194799.0	Manual	Sedan	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Toyota	1
2	1497	Supra	Black	24069281	194799.0	Manual	Sedan	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Toyota	1
3	1891	Supra	Blue	21828354	194799.0	Manual	Sedan	27.0	211287.0	True	-1.648800e+04	-8.464109e-02	Toyota	1
4	1955	Supra	Black	25620849	194799.0	Manual	Sedan	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Toyota	1
5	2435	Supra	Blue	19606492	194799.0	Manual	Sedan	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Toyota	1
6	2645	Supra	White	21322640	194799.0	Manual	Sedan	12.0	216338.0	False	-2.153900e+04	-1.105704e-01	Toyota	1
7	3640	Supra	Black	27858456	194799.0	Manual	Sedan	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Toyota	1
8	3743	Supra	Red	20518362	194799.0	Manual	Sedan	13.0	212860.0	True	-1.806100e+04	-9.271608e-02	Toyota	1
9	4405	Supra	White	24583516	194799.0	Manual	Sedan	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Toyota	1

Last rows

	car_id	car_type	color	km	average_price	transmission	body_type	DI	price	sold	diff_price	diff_price_perc	card_brand	antiquity
19990	14019	S80	Blue	12582104	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19991	15396	S80	Red	18468745	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19992	15629	S80	Blue	15260331	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19993	15855	S80	White	14868440	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19994	16169	S80	Black	14111995	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19995	16468	S80	Black	14232987	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19996	16971	S80	Black	18144875	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19997	17013	S80	Red	16447711	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19998	18235	S80	Red	11665859	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7
19999	18543	S80	Black	18127179	142081.0	Automatic	SUV	NaN	NaN	NaN	-1.010101e+09	-1.010101e+09	Volvo	7

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Latin 1 Sup

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Interactions

Correlations

Pearson's r